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# Data Engineer - Databricks / Pyspark

- **Company:** AXPE CONSULTING
- **Location:** Madrid, Spain
- **Salary:** €38,000.0 - €50,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Python (Programming Language), SQL Databases, Data Streaming, Google Cloud, Apache Spark, Data Lakes, Pyspark, Data Analytics, Apache Kafka, Terraform, Databricks
- **Published:** September 12, 2026
- **Apply:** https://eurojobs.com/jobs/27019634/apply

## About the Role

Experiencia profesional como Data Engineer / Big Data Engineer.

Desarrollo con Python y PySpark.

Experiencia con Apache Spark.

Buen nivel de SQL.

Experiencia con Databricks o plataformas equivalentes.

Diseño, desarrollo y mantenimiento de pipelines ETL/ELT.

Experiencia trabajando con grandes volúmenes de datos.

¿Qué conocimientos suman?

Airflow.

Kafka y arquitecturas Streaming.

Delta Lake / arquitecturas Lakehouse.

AWS, Azure o GCP.

S3, Glue, EMR, Athena, ADF.

Terraform / Infrastructure as Code.

CI/CD aplicado a Data.

Scala.

Experiencia en banca, fintech o servicios financieros., Crecimiento técnico y profesional dentro de proyectos Data de gran escala.

## Description

Los datos están en el centro de algunas de las transformaciones tecnológicas más importantes de las grandes organizaciones.

En AXPE Consulting seguimos reforzando nuestra práctica de Data & Analytics y queremos conocer profesionales con experiencia en ingeniería de datos que quieran seguir creciendo en proyectos de gran escala.

Participamos en entornos donde tecnologías como Databricks, Spark, PySpark y Cloud tienen un papel protagonista: construcción y evolución de plataformas Data, procesamiento de grandes volúmenes de información, pipelines de datos y arquitecturas Data Lake / Lakehouse.

Buscamos Data Engineers para proyectos actuales y futuros, con interés en continuar evolucionando técnicamente y afrontar nuevos retos dentro del ecosistema Data.


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